Graduate Studies in Computer Science at Dalhousie...

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Graduate Studies in Computer Science at Dalhousie University

Evangelos MiliosFaculty of Computer Science

Dalhousie Universitywww.cs.dal.ca/~eem

Bird’s eye view of Halifax

Halifax Fun

Halifax, Nova Scotia

• Northernmost harbour that does not freeze in the winter

• Relatively mild climate• Metropolis of Atlantic Canada (incl. Nova

Scotia, New Brunswick, Prince Edward Island, and Newfoundland)

• Regional economic, cultural and research hub

• Settled by Europeans in the 18th century

Dalhousie U. Facts• Founded in 1818• The smallest Medical/Doctoral university in Canada

– Medical school– Law school– Engineering– Business school

• World class– Oceanography– Biology– Medicine– Sciences

• Regional Research Hub for Atlantic Canada

Faculty of Computer Science

Faculty of Computer Science• Established in 1997• Strengths in:

– Information retrieval, text mining– Health informatics & Knowledge management– Bioinformatics– Human-computer interaction– Computer networks, network management,

intrusion detection– Algorithms, graph theory, parallel computation

Interdisciplinary outlook• Master’s degrees in:

– Computer Science– Health informatics (with Medicine)– Electronic commerce (with Business and Law)– Bioinformatics (with Biology)

• Joint research projects with– Mathematics– Engineering– Medicine– Business– Biology

Research overview

Research snippets

Networked Information Spaces:

Modellingand

Mining

Documents are networked into information spaces

• World Wide Web• Blog space• Scientific and Medical Literature• Patents• Common Law

Desktop of the future

Peer-to-Peer Document ManagementV. Keselj, E. Milios, S. Abidi

Automatic Topic ExtractionE. Milios

Experience ManagementE. Milios, N. Zincir-Heywood

Connectivity of the Citation graphJ. Janssen, E. Milios

Strong Health

Health with Shopping

Web Page Categorization Using PCAMichael Shepherd, Carolyn Watters, Jack Duffy ……………………..

Web Information Filtering Lab (www.cs.dal.ca/wifl) ……………….

Recall and Precision > 0.80

Author 1

Author 2

Author n

Author 1Profile

Author 2Profile

Author nProfile

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Authorship Attribution using Character N-grams

Vlado Keselj

_th 0.015___ 0.013the 0.013he_ 0.011and 0.007

Dickens: Christmas Carol_th 0.016the 0.014he_ 0.012and 0.007nd_ 0.007

Dickens: A Tale of Two Cities

_th 0.017___ 0.017the 0.014he_ 0.014ing 0.007

Carroll: Alice’s adventures in wonderland

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?

#AttackConnections

#NormalConnections

NIMShttp://www.cs.dal.ca/projectx

Network Traffic ClassificationNur Zincir-Heywood

EDGE LabDalhousie University

Dr. Kori Inkpen

Exploring effective interaction techniques and input devices for richface-to-face environments

Enhancing Face-to-Face Collaboration

Aware HomeJacob Slonim

Visual Computing & DesignPhil Cox

• The role of visualisation in software development

– Visual programming languages (VPL)– Visualisation of execution– End-user and domain-specific programming

• Some projects– Design of structured objects– Programming by demonstration– VPLs for industrial software development– Spreadsheet programming and templating

• Example: Gaussian elimination for solving sets of linear equation (not a typical usual end-user application!)...

Worksheet• like an Excel worksheet• we’ve set up an array containing the

coefficients and right-hand sides of the equations

Program sheet• visual rules define templates for worksheet arrays• determine array structure, and relationships between

arrays in terms of shape and content (formulae)• gauss has two parameters, the equation array A and

the output vector C

Applying a template• select the template to apply -

gauss• select arrays in the worksheet

corresponding to the parameters of gauss

• outlines turn green when shapes are acceptable

• click the “apply” button

Applying a template• contents of solution vector (formulae) are computed, and

evaluated

Bio-informaticsOptimizing confidence intervals in phylogenyParallel Computing in protein phylogenySequence alignment curation using Artificial IntelligenceA C++ bioinformatics libraryInteractive PhylogenyProtein Biophysics and the substitution processStructural EvolutionFolding of protein loops

Dr. Christian Blouin

Dr. Thomas Trappenberg

Computational Neuroscience

Machine Learning &Data Mining

eCommerce

NICHE Research Group

(kNowledge Intensive Computing for

Healthcare Enterprises)

Raza Abidi

Research Focus is Interdisciplinary

– Computer Science• Knowledge management

– Semantic Web & Ontologies• Intelligent personalization

– Semantic web service composition– Dynamic context-sensitive information (content) personalization

– Health Informatics• Clinical decision support systems• Health knowledge modeling

– Clinical practice guidelines– Clinical pathways

• Knowledge translation• Health data mining

Key Health Informatics Projects • Knowledge translation in pediatric pain

– Web 2.0, Social network analysis• Point-of-care decision-support system

for breast-cancer follow-up– Semantic web, Reasoning engines

• Care planning for prostate cancer through Care Maps– Semantic web, planning systems

• Glaucoma detection from optic discs analysis– Data mining, Image analysis

• Knowledge sharing patterns in Emergency Department– Knowledge management

• Personalized patient educational program for cardiovascular diseases– Adaptive hypermedia, AI

Data Collection Data Storage Data Communication

Data Analysis Information Flow

Knowledge Capture Knowledge Conversion

Knowledge Connection Knowledge Operationalization

Healthcare Services

Evaluation Studies

System Deployment Standards

Policy Development Outcome Measurement

Health Informatics Research Landscape

Knowledge Morphing“The intelligent and autonomous fusion/integration of contextually, conceptually and functionally related knowledge objects that may exist in different representation modalities and formalisms, in order to establish a comprehensive, multi-faceted and networked view of all knowledge pertaining to a domain-specific problem”

AdWISE: Adaptive Web Information and Services Environment

• Intelligent Content Personalization

– AI Techniques– IR Techniques

• Applications– Personalized music playlists– Personalized news items – Personalized cardiovascular risk management

recommendations

Adaptive Personalized Care Planning via a Semantic Web

Framework• CarePlan is a

rich temporal, process-centric, patient-specific clinical pathway that manages the evolving dynamics of a patient to meet the patient’s needs, institutional workflows and medical knowledge.

Decision Support Systems

• Semantic Web Approach– Knowledge

Modeling• Ontologies

– Knowledge Execution

• Ontology based (logical) decision rules

• Logic based proof engines

• Trusted Solutions

The Dalhousie Graphics and Visualization Lab

The Graphics and Visualization Lab

• The focus is on both: – the development of new graphical techniques, and – the application of those techniques, often in cross-

disciplinary areas

• Our lab incorporates expertise in areas such as: – image processing– 3D computer graphics– physically-based rendering– visualization – and, traditional art

Graduate Courses & Faculty Members

• Visualization (6406) – focuses on graphical techniques for data

visualization that assist in the extraction of meaning from datasets

• Advanced Computer Graphics (6604) – covers topics in computer graphics,

including rendering, geometric modeling, and computer animation

• Digital Image Processing (6602) – covers topics in digital picture processing

such as visual perception, digitization, compression and enhancement

Genetic Programming

QuickTime™ and a decompressor

are needed to see this picture.

ProblemDecomposition

Co-evolutionary behaviors

Evolving Computer Programs

Game Strategy Learning MalcolmHeywood

Evolutionary Computation• evolutionary algorithms are

optimisation strategies “gleaned from nature”

• areas of application range from engineering design and control to financial forecasting and art

• research of Dalhousie’s Evolutionary Computation group focuses on understanding, improving, and developing adaptive strategies

• contact: Dr. Dirk Arnold(http://www.cs.dal.ca/˜dirk)

Dirk Arnold

Fault-tolerant networks

• Design and Reconfiguration of fault-tolerant networks.

• Objectives: construct a network that– Can continue to operate in the presence of certain

faults, – Is optimal or near-optimal in cost,

• Cost will depend on the parameters to be optimized

• Efficiency of reconfiguration measured by the time needed to identify a healthy sub-graph of the network (that excludes the defective components).

Zizo Farrag

Disk I/O bottleneck when processing massive datasets

Low cache efficiency in traditional algorithms

Need algorithms with high access locality to

Take advantage of cachesTake advantage of disk read-ahead

Techniques fundamentallydifferent from traditional algorithms!

Norbert ZehCanada Research Chair in Algorithms for Memory Hierarchies

Geometric problemsDatabases (range queries, etc)GIS (map overlay, window queries, etc)...

Graph problemsWeb modelingGIS (route planning, logistics)Bioinformatics (protein clustering, etc)...

Norbert ZehCanada Research Chair in Algorithms for Memory Hierarchies

Graduate School Information

Admission requirements

• Grade point average at least 3.7 (on a 4.3 scale)

• Strong reference (recommendation) letters• Publications highly desired (for the PhD

program)• TOEFL• GRE (optional)

Application process

• Visit: http://www.cs.dal.ca/graduate/• Deadline: January 10 (for September)• Students need support from a prospective

supervisor to be admitted– Feel free to contact faculty members in your

areas of interest two weeks after you have sent your application

– Acceptable to switch supervisors after admission– Minimal delay if done within the 8 months

How much money do I need?

18723-- total3248Teaching assistantship9324Research assistantship6151Scholarship

SUPPORT18706-- total2100Personal+books8400Housing+food8206Tuition+health ins.

EXPENSES

How much money do I need?

• Cost of living differs among Canadian cities.

• $20,000 in Halifax is the same as:

30600Ottawa30000Montreal22300Hamilton32600Toronto31000Vancouver23800EdmontonAmountCity

Data from: http://www.usask.ca/cgsr/comparison.php

How to choose a thesis topic?

• a good thesis topic is interesting:– to you, – to your advisor, and – to the research community

• Professors may have – Well defined long-term research programs

and expect their students to contribute directly– Much looser, but still related ongoing projects. – Tendency to take on anyone with an

interesting idea (beware of advisor lack of commitment)

From: How to succeed in graduate school (by Marie deJardins, SRI International)

How to choose a thesis topic?• Awareness & Reading

– Be selective: you'll never be able to read everything that might be relevant

– Become and stay aware of directly related research

• Topic options– narrow, well defined topic.

• Plus: finish fast• Minus: it may not be as exciting

– Exotic topic• Plus: potentially exciting• Minus: difficulty convincing people it's worthwhile.

How to choose a thesis topic?

• Solve a real problem, not a toy problem • Choose:

– a central problem that's solvable and acceptable,

– with extensions and additions that are ``successively riskier and that will make the thesis more exciting.

For more information• WWW: http://www.cs.dal.ca/graduate/• Email: grad@cs.dal.ca• Dalhousie Research Newsletter:

http://www.dal.ca/research/outfront/• Resources about graduate school, thesis

writing, how to do research, how to give presentations, academic job interview preparation.http://users.cs.dal.ca/~eem/gradResources/gradResources.htm